Enables fast natural language search of vectorized Markdown documents within an MCP-compatible environment.
Sponsored
RAGDB is a RAG (Retrieval-Augmented Generation) system designed to work with MCP (Minecraft Protocol) compatible chats. It allows users to store and search Markdown documents by converting them into vector embeddings. This enables natural language queries to quickly retrieve relevant information. It supports LibSQL for local file-based operation, Qdrant for cloud-based large-scale data, and PostgreSQL for large-scale data (under testing). It integrates seamlessly with MCP chats, allowing document management directly from within the chat environment.
Key Features
01Stores Markdown files as vector embeddings for efficient RAG
02Supports natural language search queries
03Compatible with LibSQL, Qdrant, and PostgreSQL databases
04Integrates with MCP-compatible chat environments
05Allows document management directly from chat
060 GitHub stars
Use Cases
01Quickly find relevant information within a large collection of Markdown documents using natural language queries.
02Create a searchable knowledge base accessible via chat commands.
03Manage and search documentation within an MCP-compatible chat environment.
